Big data management and analysis system for legal affair information

Abstract

The invention discloses a big data management and analysis system for legal affair information, which comprises a client information terminal, a wireless transmission module, a data management system, a data optimization module, a data storage terminal and a legal affair information terminal, and relates to the technical field of data management and analysis. According to the big data management and analysis system aiming at the legal affair information, the data management system is arranged to receive data of clients, and consulting and extracting operation of the data is completed through data processing according to weight templates of legal affair aiming at different events; and marking data items lacked in the weight template after traversal, and sending the data items to a client information end for one-time filling, so that data management can be specifically realized, filling compensation with a client can be completed in one-time file based on event data acquisition, the data accuracy is improved, and the user experience is improved. And subsequent processing operation of clients and legal affairs is facilitated, and subsequent data use and management are also facilitated.

Description

Technical Field

[0001] The present invention relates to the technical field of data management and analysis, and in particular to a big data management and analysis system for legal information. Background Art

[0002] Food processing refers to the grain milling, feed processing, vegetable oil and sugar processing, slaughtering and meat processing, aquatic product processing, as well as processing activities of vegetables, fruits and nuts, as well as potato, dehydrated vegetable processing, and canned vegetable processing, which directly use agricultural, forestry, animal husbandry and fishery products as raw materials. It is a type of agricultural product processing industry in a broad sense. Food processing is to put edible things through certain procedures to make them more delicious or more beneficial. The process of artificially processing raw grains or other raw materials to form a new form of directly edible product is food processing.

[0003] The reference patent name is: A legal management cloud system (patent publication number: CN117196501A, patent publication date: 2023-12-08), including a project life cycle management module, a project training management module, a customer display management module and a basic management module. The project life cycle management module includes a project management knowledge base, a full-process automated access module, a project management progress control module, a project operation data efficiency analysis module and a project management data report summary module. The basic management module includes a key management personnel account allocation and authority management module, a personnel flow project handover module and a communication and collaboration module. The project management data report summary module is provided with a project data performance sub-module and a dimensional indicator setting sub-module, which can effectively grasp the project progress, project information synchronization, high task execution efficiency, low learning cost and low handover cost.

[0004] Based on the description in the above documents, in the existing legal information management operations, especially those involving the interactive management operations of the preliminary data between the client and the legal side, the client is not aware of the importance of the specific data of the event, and when the legal side finds that a lot of important data is missing after checking, it is necessary to communicate with the client one by one, resulting in a delay in the interactive management of the data, and the data is not accurate enough to affect the subsequent management operations. For this reason, the present invention provides a big data management and analysis system for legal information. Summary of the invention

[0005] In view of the deficiencies in the prior art, the present invention provides a big data management and analysis system for legal information, which solves the problem in existing legal information management operations, especially the interactive management operations involving preliminary data between clients and legal parties. Clients are unaware of the importance of the specific data of an event, and when the legal party finds that a lot of important data is missing after checking, it needs to communicate with the clients one by one, resulting in delays in the interactive management of data and the problem that the data is not accurate enough, affecting subsequent management operations.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solutions: A big data management and analysis system for legal information, comprising:

[0007] The customer information terminal contains the demand data and actual data about the event and transmits it to the data management system;

[0008] Wireless transmission module, which realizes remote data transmission and data storage through wireless communication technology;

[0009] The data management system receives the customer's data, completes the data review and extraction operations according to the legal weight template for different events and through data processing, and then marks the missing data items in the weight template after traversal and sends them back to the customer information end for one-time filling. After the filling is completed, the data is filled again;

[0010] The data optimization module transmits the data filled in by the customer information end and fills it into the data management system to form a weighted template with data;

[0011] Data storage terminal, used for collecting data generated by the client information terminal and the legal information terminal, and storing data processed by the data management system;

[0012] The legal information end generates weight templates for different events, receives customer information, and implements event processing operations based on customer information.

[0013] Preferably, the data management system comprises:

[0014] The data conversion and storage module converts the voice data into text data, and the original data and the converted data are stored in the data storage terminal;

[0015] The data query and extraction module performs a query operation on the converted text data, matches the corresponding weight template, implements the text data content extraction operation based on the weight template and through data processing, and marks the unfilled data items;

[0016] The data feedback and sending module sends the missing data items in the weight template to the customer information end, and sends the matched data to the legal information end.

[0017] Preferably, the operation of the data conversion and storage module converting the voice data into text data is:

[0018] A1. Complete the extraction of voice data, frame the voice data, and segment it into multiple voice segments;

[0019] A2, extracting text matching data sets from the data storage terminal and identifying corresponding voice segments, and converting the voice segments into text data one by one;

[0020] A3. Sort the text data according to the order of the corresponding voice segments to form converted text data.

[0021] Preferably, the data review and extraction module performs the review operation on the converted text data as follows:

[0022] B1. Establish a repair model through sentence structure and language expression, and introduce the converted text data into the repair model;

[0023] B2. Modify the contents in the text data that are semantically incoherent or produce erroneous symbols accordingly, and obtain the required text data set, which is marked as M;

[0024] B3. Extract the main content summary based on the content expressed in the text data set M, and match the weight template that the corresponding legal terminal should provide based on the content summary.

[0025] Preferably, the data review and extraction module implements the extraction operation of the text data content according to the weight template and through data processing:

[0026] C1. Extract the types of content corresponding to different weight ratios according to the weight template, and sort them according to the weight ratios for subsequent data extraction operations;

[0027] C2. According to the sorted type content, the content in the text data set M is recognized and extracted, and the extracted features are introduced into the type content corresponding to the weight template for data filling, and the next type content extraction operation is performed after the filling is completed;

[0028] C3. After completing the content recognition operation for all types of content in the text data set M, a weight template with data is formed, and data with other presentation methods are added to the weight template of the corresponding type of content.

[0029] Preferably, the specific operation of realizing recognition and extraction of the content in the text data set M in C2 is:

[0030] c21. Match the type content corresponding to the weight template with the text data set M, find the same or similar type titles, determine the location of the data content to be extracted and mark it;

[0031] c22. Set an extraction window labeled N(x, y), where x represents the length of the extraction window and y represents the width of the window. Based on the content extraction position corresponding to the mark of the text data set M, perform an expansion operation on the extraction window N(x, y);

[0032] c23, and compare x with the length of the data content text, and compare y with the width of the data content text, and the data content text length is marked as p, and the data content text width is marked as q, and expansion operations are performed according to different situations;

[0033] c24. Extract each line of the content based on the expanded extraction window until all marked content positions are extracted.

[0034] Preferably, the specific expansion operation in c23 is:

[0035] d1. When x<p, y≥q, it is only necessary to extend the length of the extraction window;

[0036] d2. When x≥p, y<q, it is only necessary to expand the width of the extraction window and compare the text width of each line of the selected data, and select the largest data content text width q max as the width of the extraction window;

[0037] d3. When x<p, y<q, it is necessary to expand both the length and width of the extraction window, and compare the text width and length of each line of the selected data, and select the largest data content text width q max and the maximum data content text length p max as the extraction window width and the extraction window length.

[0038] Preferably, the specific expression for identifying and extracting the operation in C2 is:

[0039]

[0040] F represents the content extracted for the corresponding type of title, N(x, y n ) represents the data content under the nth line at the desired extraction position, and n represents the number of lines corresponding to the content at the desired extraction position;

[0041] That is, the expanded extraction operation expression is:

[0042]

[0043] Preferably, the data review and extraction module marks the unfilled data items as follows:

[0044] E1. By checking the weight template with data, mark the data items that are not filled with data or are missing data in the corresponding weight template;

[0045] E2. Annotate the specific textual description structure and sample content corresponding to the marked data item, combine them to form an unfilled data template and send it to the client terminal for supplementary operation.

[0046] Preferably, the specific operations of the data optimization module are:

[0047] After checking the corresponding unfilled data template, the customer enters the corresponding content according to the remarks;

[0048] Then, under the transmission of the data optimization module, the weight template with data is directly optimized, and the corresponding content is added into the weight template to form a weight template with complete data.

[0049] The present invention provides a big data management and analysis system for legal information. Compared with the prior art, it has the following beneficial effects:

[0050] (1) The big data management and analysis system for legal information is provided with a data management system to receive customer data, and completes the data review and extraction operations according to the weight templates of the legal department for different events through data processing, and then marks the missing data items in the weight template after traversal and sends them back to the customer information end for one-time filling. After the filling is completed, the data is filled again. In this way, not only can the data management be implemented in a targeted manner, but also based on the acquisition of event data, the filling compensation can be completed with the customer in one file at one time, thereby improving the accuracy of the data, facilitating the subsequent processing operations of the customer and the legal department, and also facilitating the subsequent use and management of the data.

[0051] (2) The big data management and analysis system for legal information is provided with a data review and extraction module. By reviewing the converted text data, the corresponding weight template is matched, and the text data content is extracted according to the weight template and through data processing, and the unfilled data items are marked, so that data can be extracted through the extraction window. It can be applied to texts of different types or formats, accurately complete data identification and extraction operations, and realize legal information data management and analysis operations.

[0052] (3) The big data management and analysis system for legal information is provided with a data optimization module. Under the transmission of the data optimization module, the weight template with data is directly optimized, and the corresponding content is added to the weight template to form a weight template with complete data. In this way, the weight template can be directly improved according to the marked unfilled items, eliminating the intermediate extraction steps, making the data processing operation more efficient, and at the same time, the efficiency of the previous data interaction collection operation is also improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] Figure 1 It is a principle block diagram of the data management and analysis system of the present invention;

[0054] Figure 2 is an operation flow chart of the data conversion and storage module of the present invention;

[0055] Figure 3 It is an operation flow chart of the data search and extraction module of the present invention;

[0056] Figure 4 Operational flow chart for content identification and extraction of the present invention. DETAILED DESCRIPTION

[0057] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0058] See also Figure 1-Figure 4 , the present invention provides two technical solutions:

[0059] Embodiment 1: A big data management and analysis system for legal information, comprising:

[0060] The customer information terminal contains the demand data and actual data about the event and transmits it to the data management system;

[0061] Wireless transmission module, which realizes remote data transmission and data storage through wireless communication technology;

[0062] The data management system receives the customer's data, completes the data review and extraction operations according to the legal weight template for different events and through data processing, and then marks the missing data items in the weight template after traversal and sends them back to the customer information end for one-time filling. After the filling is completed, the data is filled again;

[0063] The data optimization module transmits the data filled in by the customer information end and fills it into the data management system to form a weighted template with data;

[0064] Data storage terminal, used for collecting data generated by the client information terminal and the legal information terminal, and storing data processed by the data management system;

[0065] The legal information end generates weight templates for different events, receives customer information, and implements event processing operations based on customer information.

[0066] Among them, by setting up a data management system, receiving customer data, and completing data review and extraction operations according to the legal weight template for different events and through data processing, then marking the missing data items in the weight template after traversal and sending them as feedback to the customer information end for one-time filling, and then filling the data after the filling is completed. In this way, not only can the data management be realized in a targeted manner, but also based on the acquisition of event data, the filling compensation can be completed with the customer in one file at one time, thereby improving the accuracy of the data, facilitating the subsequent processing operations of customers and legal affairs, and also facilitating the subsequent use and management of data.

[0067] In an embodiment of the present invention, the data management system includes:

[0068] The data conversion and storage module converts the voice data into text data, and the original data and the converted data are stored in the data storage terminal;

[0069] The data query and extraction module performs a query operation on the converted text data, matches the corresponding weight template, implements the text data content extraction operation based on the weight template and through data processing, and marks the unfilled data items;

[0070] The data feedback and sending module sends the missing data items in the weight template to the customer information end, and sends the matched data to the legal information end.

[0071] In the embodiment of the present invention, the operation of the data conversion and storage module to convert the voice data into text data is as follows:

[0072] A1. Complete the extraction of voice data, frame the voice data, and segment it into multiple voice segments;

[0073] A2, extracting text matching data sets from the data storage terminal and identifying corresponding voice segments, and converting the voice segments into text data one by one;

[0074] A3. Sort the text data according to the order of the corresponding voice segments to form converted text data.

[0075] In the embodiment of the present invention, the data review and extraction module performs the review operation on the converted text data as follows:

[0076] B1. Establish a repair model through sentence structure and language expression, and introduce the converted text data into the repair model;

[0077] B2. Modify the contents in the text data that are semantically incoherent or produce erroneous symbols accordingly, and obtain the required text data set, which is marked as M;

[0078] B3. Extract the main content summary based on the content expressed in the text data set M, and match the weight template that the corresponding legal terminal should provide based on the content summary.

[0079] In the embodiment of the present invention, the data query and extraction module implements the extraction operation of the text data content according to the weight template and through data processing as follows:

[0080] C1. Extract the types of content corresponding to different weight ratios according to the weight template, and sort them according to the weight ratios for subsequent data extraction operations;

[0081] C2. According to the sorted type content, the content in the text data set M is recognized and extracted, and the extracted features are introduced into the type content corresponding to the weight template for data filling, and the next type content extraction operation is performed after the filling is completed;

[0082] C3. After completing the content recognition operation for all types of content in the text data set M, a weight template with data is formed, and data with other presentation methods are added to the weight template of the corresponding type of content.

[0083] In the embodiment of the present invention, the specific operation of realizing recognition and extraction of the content in the text data set M in C2 is:

[0084] c21. Match the type content corresponding to the weight template with the text data set M, find the same or similar type titles, determine the location of the data content to be extracted and mark it;

[0085] c22. Set an extraction window labeled N(x, y), where x represents the length of the extraction window and y represents the width of the window. Based on the content extraction position corresponding to the mark of the text data set M, perform an expansion operation on the extraction window N(x, y);

[0086] c23, and compare x with the length of the data content text, and compare y with the width of the data content text, and the data content text length is marked as p, and the data content text width is marked as q, and expansion operations are performed according to different situations;

[0087] c24. Extract each line of the content based on the expanded extraction window until all marked content positions are extracted.

[0088] Among them, by setting up a data review and extraction module, the converted text data is reviewed and matched with the corresponding weight template. The text data content is extracted according to the weight template and through data processing, and the unfilled data items are marked. In this way, data is extracted through the extraction window, which can be applied to texts of different types or formats, accurately complete data identification and extraction operations, and realize legal information data management and analysis operations.

[0089] In the embodiment of the present invention, the specific expansion operation in c23 is:

[0090] d1. When x<p, y≥q, it is only necessary to extend the length of the extraction window;

[0091] d2. When x≥p, y<q, it is only necessary to expand the width of the extraction window and compare the text width of each line of the selected data, and select the largest data content text width q max As the width of the extraction window;

[0092] d3. When x<p, y<q, it is necessary to expand both the length and width of the extraction window, and compare the text width and length of each line of the selected data, and select the largest data content text width q max and the maximum data content text length p max as the extraction window width and the extraction window length.

[0093] In the embodiment of the present invention, the specific expression of the identification and extraction operation in C2 is:

[0094]

[0095] F represents the content extracted for the corresponding type of title, N(x, y n ) represents the data content under the nth line at the desired extraction position, and n represents the number of lines corresponding to the content at the desired extraction position;

[0096] That is, the expanded extraction operation expression is:

[0097]

[0098] In the embodiment of the present invention, the data search and extraction module marks the unfilled data items as follows:

[0099] E1. By checking the weight template with data, mark the data items that are not filled with data or are missing data in the corresponding weight template;

[0100] E2. Annotate the specific textual description structure and sample content corresponding to the marked data item, combine them to form an unfilled data template and send it to the client terminal for supplementary operation.

[0101] In the embodiment of the present invention, the specific operations of the data optimization module are:

[0102] After checking the corresponding unfilled data template, the customer enters the corresponding content according to the remarks;

[0103] Then, under the transmission of the data optimization module, the weight template with data is directly optimized, and the corresponding content is added into the weight template to form a weight template with complete data.

[0104] Among them, by setting up a data optimization module, the weight template with data can be directly optimized under the transmission of the data optimization module, and the corresponding content can be added to the weight template to form a weight template with complete data. In this way, according to the marked unfilled items, the weight template can be directly improved, eliminating the intermediate extraction steps, making the data processing operation more efficient, and at the same time, the efficiency of the previous data interaction collection operation is also improved.

[0105] The difference between the second embodiment and the first embodiment is that:

[0106] By applying the existing big data management and analysis system for legal information and the big data management and analysis system for legal information of the present invention to multiple identical clients and legal terminals, the data of the actual events of the clients are transmitted to the legal terminals, wherein the time required by the clients is the normal time and is not delayed by other events. After the feedback arrives, the data filling operation is performed, and the completeness of the event data and the data required by the legal department is recorded, as well as the time from data reception to the completion of the event data to the allocation. The specific results are shown in Table 1:

[0107] Table 1 Situation table

[0108] Average data filling completeness Average initial data processing time Existing data management and analysis systems 68％ 43min Data management and analysis system of the present invention 98％ 15min

[0109] To sum up, the big data management and analysis system for legal information of the present invention is applied to multiple identical clients and legal terminals to achieve higher completeness of event data filling, and takes less time for preliminary data processing. The data management and analysis operations that can be completed are more efficient, and the management and analysis operations of legal information can be better realized.

[0110] Meanwhile, the contents not described in detail in this specification belong to the prior art known to those skilled in the art.

[0111] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0112] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A big data management and analysis system for legal information, characterized by: include: The customer information terminal contains the demand data and actual data about the event and transmits it to the data management system; Wireless transmission module, which realizes remote data transmission and data storage through wireless communication technology; The data management system receives the customer's data, completes the data review and extraction operations according to the legal weight template for different events and through data processing, and then marks the missing data items in the weight template after traversal and sends them back to the customer information end for one-time filling. After the filling is completed, the data is filled again; The data optimization module transmits the data filled in by the customer information end and fills it into the data management system to form a weighted template with data; Data storage terminal, used for collecting data generated by the client information terminal and the legal information terminal, and storing data processed by the data management system; The legal information end generates weight templates for different events, receives customer information, and implements event processing operations based on customer information.

2. The big data management and analysis system for legal information according to claim 1, characterized in that: The data management system comprises: The data conversion and storage module converts the voice data into text data, and the original data and the converted data are stored in the data storage terminal; The data query and extraction module performs a query operation on the converted text data, matches the corresponding weight template, implements the text data content extraction operation based on the weight template and through data processing, and marks the unfilled data items; The data feedback and sending module sends the missing data items in the weight template to the customer information end, and sends the matched data to the legal information end.

3. The big data management and analysis system for legal information according to claim 2, characterized in that: The data conversion and storage module converts the voice data into text data by: A1. Complete the extraction of voice data, frame the voice data, and segment it into multiple voice segments; A2, extracting text matching data sets from the data storage terminal and identifying corresponding voice segments, and converting the voice segments into text data one by one; A3. Sort the text data according to the order of the corresponding voice segments to form converted text data.

4. The big data management and analysis system for legal information according to claim 2, characterized in that: The data review and extraction module performs the following review operations on the converted text data: B1. Establish a repair model through sentence structure and language expression, and introduce the converted text data into the repair model; B2. Modify the contents in the text data that are semantically incoherent or produce erroneous symbols accordingly, and obtain the required text data set, which is marked as M; B3. Extract the main content summary based on the content expressed in the text data set M, and match the weight template that the corresponding legal terminal should provide based on the content summary.

5. The big data management and analysis system for legal information according to claim 4 is characterized by: The data review and extraction module implements the extraction operation of text data content according to the weight template and through data processing as follows: C1. Extract the types of content corresponding to different weight ratios according to the weight template, and sort them according to the weight ratios for subsequent data extraction operations; C2. According to the sorted type content, the content in the text data set M is recognized and extracted, and the extracted features are introduced into the type content corresponding to the weight template for data filling, and the next type content extraction operation is performed after the filling is completed; C3. After completing the content recognition operation for all types of content in the text data set M, a weight template with data is formed, and data with other presentation methods are added to the weight template of the corresponding type of content.

6. The big data management and analysis system for legal information according to claim 5, characterized in that: The specific operation of realizing the recognition and extraction of the content in the text data set M in C2 is: c21. Match the type content corresponding to the weight template with the text data set M, find the same or similar type titles, determine the location of the data content to be extracted and mark it; c22. Set an extraction window labeled N(x, y), where x represents the length of the extraction window and y represents the width of the window. Based on the content extraction position corresponding to the mark of the text data set M, perform an expansion operation on the extraction window N(x, y); c23, and compare x with the length of the data content text, and compare y with the width of the data content text, and the data content text length is marked as p, and the data content text width is marked as q, and expansion operations are performed according to different situations; c24. Extract each line of the content based on the expanded extraction window until all marked content positions are extracted.

7. The big data management and analysis system for legal information according to claim 6 is characterized by: The specific expansion operations in c23 are: d1. When x<p, y≥q, it is only necessary to extend the length of the extraction window; d2. When x≥p, y<q, it is only necessary to expand the width of the extraction window and compare the text width of each line of the selected data, and select the largest data content text width q max as the width of the extraction window; d3. When x<p, y<q, it is necessary to expand both the length and width of the extraction window, and compare the text width and length of each line of the selected data, and select the largest data content text width q max and the maximum data content text length p max as the extraction window width and the extraction window length.

8. The big data management and analysis system for legal information according to claim 7, characterized in that: The specific expression of the identification and extraction operation in C2 is: F represents the content extracted for the corresponding type of title, N(x, y n ) represents the data content under the nth line at the desired extraction position, and n represents the number of lines corresponding to the content at the desired extraction position; That is, the expanded extraction operation expression is:

9. The big data management and analysis system for legal information according to claim 5, characterized in that: The data review and extraction module marks the unfilled data items as follows: E1. By checking the weight template with data, mark the data items that are not filled with data or are missing data in the corresponding weight template; E2. Annotate the specific textual description structure and sample content corresponding to the marked data item, combine them to form an unfilled data template and send it to the client terminal for supplementary operation.

10. A big data management and analysis system for legal information according to claim 9, characterized in that: The specific operations of the data optimization module are: After checking the corresponding unfilled data template, the customer enters the corresponding content according to the remarks; Then, under the transmission of the data optimization module, the weight template with data is directly optimized, and the corresponding content is added into the weight template to form a weight template with complete data.

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